3D Structure Research Articles

A computational discovery of hexokinase 2 inhibitors from Newbouldia laevis for Hepatocellular carcinoma (HCC) treatment

Newbouldia laevis, also known as the African Border Tree or Fever Tree, is a deciduous tree native to West Africa. The plant is valued for its medicinal properties and is used in traditional medicine for its antimicrobial and anti-inflammatory effects. N. laevis, is a storage tank of phytochemicals with huge health benefits and performances globally for the treatment and management of numerous disease conditions. Limited research exists on the usage of N. laevis for hepatocellular carcinoma (HCC) treatment. This study aims to explore the inhibitory activities of phytochemicals from N. laevis against the hexokinase 2 protein, a target in hepatocarcinoma (HCC) treatment. This study presents a unique in silico approach that includes ligand binding site prediction, molecular docking, molecular dynamics simulation, and Molecular Mechanics Poisson–Boltzmann Surface Area (MM/PBSA) methods. A total of 35 phytochemicals with available 3D structures were identified through literature mining. The literature review highlighted the significance of hexokinase 2 protein as a target inhibitor in the treatment of hepatocellular carcinoma (HCC). Molecular docking experiment with the all the identified phytochemicals and hexokinase 2 revealed that all the identified phytochemicals had potential inhibitory activities against the target protein. Moreover, chrysarobin, apigenin and ursolic acid were the best inhibitors with lowest binding energy of −8.9 kcal/mol, −8.7 kcal/mol, and −8.5 kcal/mol, respectively. The docking experiment was validated by comparing the binding affinities with known reference drug Cabozantinib-S-malate (−8.3 kcal/mol). Further, molecular dynamics studies of complexes with the best docking scores and reference drug complexes were described in detail here. The results of 100 ns modeling (RMSD, RMSF, Rg and SASA) show extraordinary stability during the establishment of complexes with apigenin and ursolic acid, as well as favorable binding energy, which was determined theoretically by means of the MM/PBSA method, thereby increase the probability of their acting as promising and likely hexokinase 2 inhibitors. Therefore, the study predicted that apigenin and ursolic acid could be used as a potential inhibitor/antagonist for the hexokinase 2 enzyme.

State-of-the-RNArt: benchmarking current methods for RNA 3D structure prediction.

RNAs are essential molecules involved in numerous biological functions. Understanding RNA functions requires the knowledge of their 3D structures. Computational methods have been developed for over two decades to predict the 3D conformations from RNA sequences. These computational methods have been widely used and are usually categorised as either ab initio or template-based. The performances remain to be improved. Recently, the rise of deep learning has changed the sight of novel approaches. Deep learning methods are promising, but their adaptation to RNA 3D structure prediction remains difficult. In this paper, we give a brief review of the ab initio, template-based and novel deep learning approaches. We highlight the different available tools and provide a benchmark on nine methods using the RNA-Puzzles dataset. We provide an online dashboard that shows the predictions made by benchmarked methods, freely available on the EvryRNA platform: https://evryrna.ibisc.univ-evry.fr/evryrna/state_of_the_rnart/.

Eosin Y derivatives for visible light-mediated free-radical polymerization: Applications in 3D-photoprinting and bacterial photodynamic inactivation

This study reports the design and the subsequent use of mono-allylated (EY-MA) and di-allylated (EY-DA) derivatives of eosin Y (EY) as highly efficient visible light-sensitive photosensitizers (PS) of bio-based H-donor molecules (cysteamine (Cys) or N-acetyl-L-cysteine (NAC)) and an electron donor (N-methyldiethanolamine, MDEA) for free-radical and thiol-acrylate polymerizations of a biobased monomer derived from soybean oil (SOA) upon exposure to visible light. High final acrylate conversions for SOA polymerization (up to 80 %) evidence the efficient photoinitiating properties of the eosin derivatives systems under irradiation with light emitting diodes (LEDs) centred at 405, 455 and 505 nm, and outperform those obtained with EY and other common photosensitizers such as camphorquinone or benzophenone. As described by fluorescence and phosphorescence analyses, laser flash photolysis (LFP) and electron paramagnetic resonance spin-trapping (EPR-ST) experiments, EY-MA and EY-DA can react via a proton/proton-coupled electron transfer reaction with Cys (or NAC) and MDEA respectively. The efficient singlet oxygen generation of the EY-MA-based materials upon exposure to visible light leads to excellent antibacterial properties, against both Gram-positive Staphylococcus aureus (S. aureus) and Gram-negative Escherichia coli (E. coli). A 3-log decrease of E. coli adhesion on the surface of the materials is observed and 100 % adhesion inhibition of S. aureus is also demonstrated. The co-polymerization of the eosin-derived PS with the polymer matrix ensures sustainable antibacterial properties against both bacteria strains upon visible light exposure as it prevents their leakage out of the polymer network. Finally, finely complex 3D structures are successfully obtained by a 3D-photoprinting technology with the investigated EY-MA-based formulation using LED@405 nm.

Application of Cell Penetrating Peptides for Intracellular Delivery of Endostatin: A Computational Approach.

Endostatin is an antiangiogenic compound with anticancer activity. The poor stability and low half-life of endostatin are the main barriers to the clinical use of this protein. Cell-penetrating peptides (CPPs) are extensively applied as carrier in the delivery of drugs and different therapeutic agents. Therefore, they can be proper candidates to improve endostatin delivery to the target cells. In this study, we aim to computationally predict appropriate CPPs for the delivery of endostatin. Potential appropriate CPPs for protein delivery were selected based on the literature. The main parameters for detection of best CPP-endostatin fusions, including stability, hydrophobicity, antigenicity, and subcellular localization, were predicted using ProtParam, VaxiJen, and DeepLoc-1.0 servers, respectively. The 3D structures of the best CPP-Endostatin fusions were modeled by the I-TASSER server. The predicted models were validated using PROCHECK, ERRAT, Verify3D and ProSA-Web servers. The best models were visualized by the PyMol molecular graphics system. Considering the principal parameters in the selection of best CPPs for endostatin delivery, endostatin fusions with four CPPs, including Cyt c-ss-MAP, TP-biot1, MPGα, and DPV1047, high stability and hydrophobicity, no antigenicity and extracellular localization were predicted as the best potential fusions for endostatin delivery. Four CPPs, including Cyt c-ss-MAP, TP-biot1, MPGα, and DPV1047, were predicted as the best potential candidates to improve endostatin delivery. Application of these CPPs may overcome the limitation of endostatin therapeutic applications, including poor stability and low half-life. Subsequent experimental studies will contribute to verifying these computational results.

Targeting Epidermal Growth Factor Receptor with Ficus virens Metabolites to Manage Cancer Progression: Molecular Docking and ADME Study

Abstract Introduction: Targeting epidermal growth factor receptor (EGFR) has been used in the treatment of several cancer types where EGFR has a notable involvement in signalling pathways. Medicinal plants are the oldest and healthiest source of medication used in modern pharmacological therapy. Previous research indicates that the compounds found in Ficus virens stem bark have significant therapeutic properties against a range of illnesses, including cancer. Therefore, in this study, molecular docking research was conducted to determine the binding interactions and affinity of secondary metabolites predicted in F. virens methanolic extract with the target protein, EGFR. Methodology: Three-dimensional (3D) conformers of the secondary metabolism products and adenosine triphosphate (ATP) were collected from PubChem on 5 January 2024. The 3D structure of EGFR and its inhibitor was retrieved from the Protein Data Bank (PDB) databank and ligands and proteins were converted to AutoDock-compatible format and then the energy minimisation was performed by the Open Babel in PyRx. Finally, using PyRx-Python 0.8, molecular docking was done, and using Discovery Studio, visualisation was done as well. The grid box dimensions were specified at 30 Å ×30 Å ×25 Å, and the physiochemical property evaluation was done by the SwissADME online server. Results: In this study, molecular docking assessed 14 compounds, including phytochemicals and ATP, for their binding with EGFR (PDB Id: 1XKK). Redocking of lapatinib validated the results. Natural chemicals showed binding energies from −4.0 to −7.8 Kcal/mol, with oleic acid and iso-caryophyllene demonstrating promising interactions, sourced from F. virens. Despite some limitations, these compounds exhibit potential for EGFR-targeted drug development, despite one Lipinski’s rule violation. Conclusions: EGFR inhibitory activities of iso-caryophyllene and oleic acid, which were identified in the F. virens methanol extract, were remarkable and higher than that of the substrate; their potential opens up exciting new possibilities for moving forward with cancer treatment. It is encouraged to further investigate the in vivo effectiveness of iso-caryophyllene, by means of animal models and cell lines.

Ablation of Sam50 is associated with fragmentation and alterations in metabolism in murine and human myotubes.

The sorting and assembly machinery (SAM) Complex is responsible for assembling β-barrel proteins in the mitochondrial membrane. Comprising three subunits, Sam35, Sam37, and Sam50, the SAM complex connects the inner and outer mitochondrial membranes by interacting with the mitochondrial contact site and cristae organizing systemcomplex. Sam50, in particular, stabilizes the mitochondrial intermembrane space bridging (MIB) complex, which is crucial for protein transport, respiratory chain complex assembly, and regulation of cristae integrity. While the role of Sam50 in mitochondrial structure and metabolism in skeletal muscle remains unclear, this study aims to investigate its impact. Serial block-face-scanning electron microscopyand computer-assisted 3D renderings were employed to compare mitochondrial structure and networking in Sam50-deficient myotubes from mice and humans with wild-type (WT) myotubes. Furthermore, autophagosome 3D structure was assessed in human myotubes. Mitochondrial metabolic phenotypes were assessed using Gas Chromatography-Mass Spectrometry-based metabolomics to explore differential changes in WT and Sam50-deficient myotubes. The results revealed increased mitochondrial fragmentation and autophagosome formation in Sam50-deficient myotubes compared to controls. Metabolomic analysis indicated elevated metabolism of propanoate and several amino acids, including ß-Alanine, phenylalanine, and tyrosine, along with increased amino acid and fatty acid metabolism in Sam50-deficient myotubes. Furthermore, impairment of oxidative capacity was observed upon Sam50 ablation in both murine and human myotubes, as measured with the XF24 Seahorse Analyzer. Collectively, these findings support the critical role of Sam50 in establishing and maintaining mitochondrial integrity, cristae structure, and mitochondrial metabolism. By elucidating the impact of Sam50-deficiency, this study enhances our understanding of mitochondrial function in skeletal muscle.

Multifunctional Applications Enabled by Fluorination of Hexagonal Boron Nitride.

2D materials exhibit exceptional properties as compared to their macroscopic counterparts, with promising applications in nearly every area of science and technology. To unlock further functionality, the chemical functionalization of 2D structures is a powerful technique that enables tunability and new properties within these materials. Here, the successful effort to chemically functionalize hexagonal boron nitride (hBN), a chemically inert 2D ceramic with weak interlayer forces, using a gas-phase fluorination process is exploited. The fluorine functionalization guides interlayer expansion and increased polar surface charges on the hBN sheets resulting in a number of vastly improved applications. Specifically, the F-hBN exhibits enhanced dispersibility and thermal conductivity at higher temperatures by more than 75% offering exceptional performance as a thermofluid additive. Dispersion of low volumes of F-hBN in lubricating oils also offers marked improvements in lubrication and wear resistance for steel tribological contacts decreasing friction by 31% and wear by 71%. Additionally, incorporating numerous negatively charged fluorine atoms on hBN induces a permanent dipole moment, demonstrating its applicability in microelectronic device applications. The findings suggest that anchoring chemical functionalities to hBN moieties improves a variety of properties for h-BN, making it suitable for numerous other applications such as fillers or reinforcement agents and developing high-performance composite structures.

PanIN or IPMN? Redefining Lesion Size in 3 Dimensions.

Pancreatic ductal adenocarcinoma (PDAC) develops from 2 known precursor lesions: a majority (∼85%) develops from pancreatic intraepithelial neoplasia (PanIN), and a minority develops from intraductal papillary mucinous neoplasms (IPMNs). Clinical classification of PanIN and IPMN relies on a combination of low-resolution, 3-dimensional (D) imaging (computed tomography, CT), and high-resolution, 2D imaging (histology). The definitions of PanIN and IPMN currently rely heavily on size. IPMNs are defined as macroscopic: generally >1.0cm and visible in CT, and PanINs are defined as microscopic: generally <0.5cm and not identifiable in CT. As 2D evaluation fails to take into account 3D structures, we hypothesized that this classification would fail in evaluation of high-resolution, 3D images. To characterize the size and prevalence of PanINs in 3D, 47 thick slabs of pancreas were harvested from grossly normal areas of pancreatic resections, excluding samples from individuals with a diagnosis of an IPMN. All patients but one underwent preoperative CT scans. Through construction of cellular resolution 3D maps, we identified >1400 ductal precursor lesions that met the 2D histologic size criteria of PanINs. We show that, when 3D space is considered, 25 of these lesions can be digitally sectioned to meet the 2D histologic size criterion of IPMN. Re-evaluation of the preoperative CT images of individuals found to possess these large precursor lesions showed that nearly half are visible on imaging. These findings demonstrate that the clinical classification of PanIN and IPMN fails in evaluation of high-resolution, 3D images, emphasizing the need for re-evaluation of classification guidelines that place significant weight on 2D assessment of 3D structures.

Site Identification and Next Choice Protocol for Hit-to-Lead Optimization.

Time efficiency and cost savings are major challenges in drug discovery and development. In this process, the hit-to-lead stage is expected to improve efficiency because it primarily exploits the trial-and-error approach of medicinal chemists. This study proposes a site identification and next choice (SINCHO) protocol to improve the hit-to-lead efficiency. This protocol selects an anchor atom and growth site pair, which is desirable for a hit-to-lead strategy starting from a 3D complex structure. We developed and fine-tuned the protocol using a training data set and assessed it using a test data set of the preceding hit-to-lead strategy. The protocol was tested for experimentally determined structures and molecular dynamics (MD) ensembles. The protocol had a high prediction accuracy for applying MD ensembles, owing to the consideration of protein flexibility. The SINCHO protocol enables medicinal chemists to visualize and modify functional groups in a hit-to-lead manner.

Analysis of the Polarization Distribution and Spin Angular Momentum of the Interference Field Obtained by Co-Planar Beams with Linear and Circular Polarization

Interference of two and four light beams with linear or circular polarization is studied analytically and numerically based on the Richards–Wolf formalism. We consider such characteristics of the interference fields as the distribution of intensity, polarization, and spin angular momentum density. The generation of light fields with 1D and 2D periodic structure of both intensity and polarization is demonstrated. We can control the periodic structure both by changing the polarization state of the interfering beams and by changing the numerical aperture of focusing. We consider examples with a basic configuration, as well as those with a certain symmetry in the polarization state of the interfering beams. In some cases, increasing the numerical aperture of the focusing system significantly affects the generated distributions of both intensity and polarization. Experimental results, obtained using a polarization video camera, are in good agreement with the simulation results. The considered light fields can be used in laser processing of thin films of photosensitive (as well as polarization-sensitive) materials in order to create arrays of various ordered nano- and microstructures.

‘5D PRINTING’ -THE NEW ERA IN DENTISTRY! -A NARRATIVE REVIEW

3D printing technology has a wide range of applications in various industries. It is widely used to produce complex 3D structures, but it has some limitations such as a limited amount of material, etc., which have been overcome with the introduction of 4D printing technology. In 4D printing, which involves time as a function and the combination of smart materials, this enables properties such as changing form and function.[1]Five-dimensional (5D) printing is a new branch of additive manufacturing (AM) with great potential to solve problems in engineering, medicine, dentistry and other related fields. It is the latest technological advancement used to produce complex and intricately shaped products, implants and devices with much better physical properties than those obtained by three-dimensional (3D) printing. The concept of 5D printing originated from William Yerazunis of the American University of Mitsubishi Electric Research Laboratories (MERL). In 5D printing, the printing plate also moves with the printing head during the printing process. in 3D printing techniques.[1]four-dimensional (4D) printing is the concept of using a smart material that can change the shape of a printed object over time as the temperature changes. [2] One of the advantages of 5D printing is the use of 25% less material than 3D printing. Five-dimensional printing is all about efficiently manufacturing this complex and curved structure with maximum strength. Using computer-aided design (CAD) data to produce super strong dental implants, orthodontic brackets, crowns, aligners, bridges and appliances. This CAD data is created using the dentist's 3D scanner / different design software.[1] 5D printing of five axes: [1], 1.X-axis ;2. Y-axis;3. Z axis; 4. Movable print head and 5. Movable printing base.5D printing is an advanced manufacturing technology that builds on the concept of 3D printing and adds customization options and features. While 3D printing requires the creation of three-dimensional objects layer by layer, 5D printing allows additional functions or features to be added to a printable object, often dynamically or responsively. its role in dentistry may be limited due to the newness of the technology.

First‐Principles Investigations of Structural, Electronic, and Elastic Properties of ZrSiO3 Perovskite: Layer Dependence, Surface Termination, and Pressure Effects

Zirconium silicate (ZrSiO3) perovskite is a promising material for various technological applications. The structural, electronic, and thermodynamic properties of ZrSiO3 perovskite are studied under different conditions, including pressure and layer configuration variations using density functional theory. The present investigation includes a thorough analysis of 2D perovskite derivatives derived from its basic 3D structure. The bulk and surface‐terminated silicon‐dominant SiO2 and zirconium‐dominant ZrO compounds are found to be mechanically stable with an anisotropy factor above 1. The calculated indirect‐bandgap values for the ZrO termination and SiO2 termination are found to be 2.585 and 1.639 eV, respectively. Moreover, the pore size of the SiO2‐terminated slab model of ZrSiO3 is calculated to be 105.39 μm and that for ZrO‐termination to be 129.30 μm. Thus, the material considered for the study can have potential applications in bone regeneration and tissue engineering. Further, the possibilities for modifying ZrSiO3 for uses in electrical devices, sensors, sustainable energy materials, and even biomedical applications like tissue engineering are intriguingly expanded by the present findings.

Fast computational approach with prior dimension reduction for three-dimensional chemical component analysis using CT data of spectral imaging.

Spectral image (SI) measurement techniques, such as X-ray absorption fine structure (XAFS) imaging and scanning transmission electron microscopy (STEM) with energy-dispersive X-ray spectroscopy (EDS) or electron energy loss spectroscopy (EELS), are useful for identifying chemical structures in composite materials. Machine-learning techniques have been developed for automatic analysis of SI data, and their usefulness has been proven. Recently, an extended measurement technique combining SI with a computed tomography (CT) technique (CT-SI), such as CT-XAFS and STEM-EDS/EELS tomography, was developed to identify the three-dimensional (3D) structures of chemical components. CT-SI analysis can be conducted by combining CT reconstruction algorithms and chemical component analysis based on machine learning techniques. However, this analysis incurs high computational costs owing to the size of the CT-SI datasets. To address this problem, this study proposed a fast computational approach for 3D chemical component analysis in an unsupervised learning setting. The primary idea for reducing the computational cost involved compressing the CT-SI data prior to CT computation and performing 3D reconstruction and chemical component analysis on the compressed data. The proposed approach significantly reduced the computational cost without losing information about the 3D structure and chemical components. We experimentally evaluated the proposed approach using synthetic and real CT-XAFS data, which demonstrated that our approach achieved a significantly faster computational speed than the conventional approach while maintaining analysis performance. As the proposed procedure can be implemented with any CT algorithm, it is expected to accelerate 3D analyses with sparse regularized CT algorithms in noisy and sparse CT-SI datasets.

Symmetry-Constrained Properties Behave Differently for 2D or 3D Structures under the Same Point Group.

In chemistry and physics, two molecules belonging to the same point group are expected to behave similarly regarding various properties, following their character tables. Here, we show that the derivative of the dipole moment with respect to the normal coordinate of vibration might show different symmetry constraints if the molecule is planar, even if these molecules belong to the same point group. Examples of pairs of molecules featuring these conditions are presented. These findings open a new path toward a much deeper understanding of how 2D materials behave so differently compared to 3D materials featuring the very same atoms and arrangements (graphene and graphite, for example); chemists and physicists dealing with 2D materials could benefit from looking more deeply into pure mathematical relations that might be governing 2D systems in a different way when compared to 3D systems. The aid from mathematicians is welcomed.

Reconfigurable 4D printing via mechanically robust covalent adaptable network shape memory polymer.

4D printing enables 3D printed structures to change shape over "time" in response to environmental stimulus. Because of relatively high modulus, shape memory polymers (SMPs) have been widely used for 4D printing. However, most SMPs for 4D printing are thermosets, which only have one permanent shape. Despite the efforts that implement covalent adaptable networks (CANs) into SMPs to achieve shape reconfigurability, weak thermomechanical properties of the current CAN-SMPs exclude them from practical applications. Here, we report reconfigurable 4D printing via mechanically robust CAN-SMPs (MRC-SMPs), which have high deformability at both programming and reconfiguration temperatures (>1400%), high Tg (75°C), and high room temperature modulus (1.06 GPa). The high printability for DLP high-resolution 3D printing allows MRC-SMPs to create highly complex SMP 3D structures that can be reconfigured multiple times under large deformation. The demonstrations show that the reconfigurable 4D printing allows one printed SMP structure to fulfill multiple tasks.

A high-precision 3D reconstruction method for the internal structure of small Solar System bodies

Small Solar System bodies (SSSBs) hold crucial information for understanding the formation and evolution of the Solar System. However, due to their considerable distance, small size, fast rotation, and a lack of prior information, the detection of these celestial bodies, especially their internal structures, faces numerous challenges. We explore whether the 3D structure of SSSBs can be reconstructed using monostatic radar. We investigated a more convenient observation mode and addressed the issue of the poor imaging quality of internal structures within existing imaging algorithms. Our study focused on a high-precision 3D imaging method for the internal structure of SSSBs based on radar signals. First, we considered a flyby observation mode that uses the spinning characteristics of the target for global observations, and we set up a scaled-down experimental system in the laboratory to simulate this observation mode. Next, we constructed a 3D printed physical surface model based on the shape of the asteroid 162173 Ryugu. We filled it with sand and inserted a small bottle containing different materials separately to construct two distinct layered analogs. The analogs were employed in laboratory measurements to acquire radar echoes, which were then inverted using both a classic back-projection (BP) algorithm and a modified multilayer back-projection (MLBP) method. The results shown that the 3D surface structure of the target can be reconstructed well through the BP and MLBP algorithms. The MLBP algorithm exhibits a higher reconstruction accuracy for internal structures. Moreover, compared to the BP method, the MLBP method is less sensitive to the quality of echo signals, resulting in a relatively stable imaging performance. Our findings reveal that observing and reconstructing the high-precision structure of SSSBs is feasible through our proposed method. The observation mode, experimental setup, and analog modeling approach are widely applicable and can be applied in future research on the detection of SSSBs with more diverse and complex structures.

Robust retrieval of forest canopy structural attributes using multi‐platform airborne LiDAR

AbstractLiDAR data acquired from airplanes and helicopters – known as airborne laser scanning (ALS) – are widely regarded as the gold standard for characterizing the 3D structure of forests at scale. But in the last decade, advances in unoccupied aerial vehicle (UAV) technologies have led to a rapid rise in the use of UAV laser scanning (ULS) for mapping forest structure. As both ALS and ULS data become increasingly available, they are being used to derive an ever‐growing number of metrics designed to measure different facets of canopy structure. However, which metrics can be robustly retrieved from both ALS and ULS platforms remains unclear. To address this question, we acquired coincident, high‐density ALS and ULS scans covering 115 plots (4‐ha in size) in an open‐canopy temperate ecosystem in Western Australia. Using this unique dataset, we quantified 32 canopy structural metrics related to canopy height, openness and heterogeneity, including metrics calculated directly from the point clouds and ones measured from derived canopy height models (CHM). Overall, we found that ALS and ULS‐derived metrics were strongly correlated (r2 = 0.90). However, this high degree of correlation masked considerable systematic differences between platforms. Specifically, point cloud metrics were less strongly (r2 = 0.87) correlated and had higher bias (10.7%) compared to CHM‐derived ones (r2 = 0.98; bias = 2.5%). Similarly, metrics of canopy openness and heterogeneity were less strongly correlated (r2 = 0.84 and 0.87) and exhibited greater bias (14.4 and 7.9%) than ones relating to canopy height (r2 = 0.96; bias = 3.8%). Our results indicate that only a small subset of the 32 metrics we tested were directly comparable between ALS and ULS platforms. Consequently, future efforts to combine laser scanning data across platforms and instruments should think carefully about which metrics are most appropriate, especially when working with point cloud data.

A new spectrally-invariant approach to the remote sensing of inhomogeneous clouds

Current operational satellite retrievals of cloud optical and microphysical properties go back to the Nakajima-King technique developed at the end of the 1980 s. This technique is based on library calculations for plane-parallel homogeneous clouds. It often works well for overcast skies but leads to substantial errors for inhomogeneous and broken cloud fields where the plane-parallel-geometry assumption is no longer valid. The basic concept of a new technique was first introduced in nuclear physics to quantify the critical conditions of reactors. Based on the eigenvalues of the radiative transfer equation, their approach provides a powerful means to parameterize the structure of 3D media. This parameterization was later successfully applied to relate surface reflectance spectra to 3D canopy structure and is known as the spectrally-invariant approximation. The proposed approach adapts this technique to the remote sensing of cloud properties such as droplet single scattering albedo and the average number of scatterings (which are the fundamental parameters in radiative transfer theory), with an emphasis on quantifying the associated errors and uncertainties. This retrieval is free from the plane-parallel homogeneous cloud assumption.

3D molecular structural modeling and characterization of indium phosphide via irregularity topological indices

Indium phosphide (InP) is a binary semiconductor composed of indium and phosphorus. It has a zinc blende crystal structure, which is a type of cubic lattice structure. This lattice is composed of indium and phosphorus atoms arranged in a lattice of cube-shaped cells, with each cell containing four indium atoms and four phosphorus atoms. This lattice structure is the same for all materials with a zinc blende crystal structure and is the most common type of lattice structure in semiconductors. Indium phosphide (InP) has several chemical applications. It is commonly used as a dopant in the production of semiconductors, where it helps control the electrical properties of the material. InP is also utilized in the synthesis various indium-containing compounds, which can have applications in catalysts and chemical reactions. Additionally, InP nanoparticles have been investigated for their potential use in biomedical imaging and drug delivery systems. The topological characterization of 3D molecular structures can be performed via graph theory. In graph theory, the connections between atoms are represented as edges and the atoms themselves are represented as nodes. Furthermore, graph theory can be used to calculate the topological descriptors of the molecule such as the degree-based and reverse degree-based irregularity toplogical indices. These descriptors can be used to compare the topology of different molecules. This paper deals with the modeling and topological characterization of indium phosphide (InP)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$({\ ext{InP}})$$\\end{document} via degree-based and reverse irregularity indices. The 3D crystal structure of the InP is topologically modeled via partition of the edges, and derived closed form expressions for its irregularity indices. Our obtained results will be surely be helpful in investigating the QSPR/QSAR analysis as well as understanding the deep irregular behavior of the indium phosphide (InP)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$({\ ext{InP}})$$\\end{document}.

Coagulating blood into adhesive gel by hybrid powder based on oppositely charged polysaccharide/tannic acid-modified mesoporous bioactive glass.

Hemostatic powder is widely utilized in emergency situations to control bleeding due to its ability to work well on wounds with irregular shapes, ease of application, and long-term stability. However, traditional powder often suffers from limited tissue adhesion and insufficient support for blood clot formation, leaving it susceptible to displacement by the flow of blood. This study introduces a hemostatic powder composed of tannic modified mesoporous bioactive glass (TMBG), cationic quaternized chitosan (QCS), and anionic hyaluronic acid modified with catechol group (HADA). The resulting TMBG/QCS/HADA based hemostatic powder (TMQH) rapidly absorbs plasma, concentrating blood coagulation factors. Simultaneously, the water-soluble QCS and HADA interact to form a 3D network structure, which can be strengthened by crosslinking with TMBG. This network effectively captures clustered blood coagulation factors, leading to a strong and adhesive thrombus that resists disruption from blood flow. TMQH exhibits superior efficacy in promoting hemostasis compared to Celox™ both in rat arterial injuries and non-compressible liver puncture wounds. TMQH demonstrates excellent antibacterial activity, cytocompatibility, and blood compatibility. These outstanding superiorities in blood clotting capability, wet tissue adhesion, antibacterial activity, safety for living organisms, ease of application, and long-term stability, make TMQH highly suitable for emergency hemostasis.